6 citations · 8 across the 6 of their papers we have counts for
5 papers · 1 filter
Difference Feature Map Distillation: Transferring Inter-Sample Relational Knowledge Towards Efficient Transformer-Based Tracking
Zhicheng Ding, Xinyu Chu, Qing Tian
In autonomous driving perception, visual object tracking systems must satisfy stringent latency and power constraints while remaining robust in complex and dynamic environments. Al…
Displacement Preserving Relational Distillation for Robust Medical Segmentation
Zhicheng Ding, Xinyu Chu, Jung Im Choi +5
Accurate 3D medical segmentation is limited by anatomical variability and high computational costs. While knowledge distillation (KD) offers a route for model compression, conventi…
Learnable Instance Attention Filtering for Adaptive Detector Distillation
Chen Liu, Qizhen Lan, Zhicheng Ding +2
As deep vision models grow increasingly complex to achieve higher performance, deployment efficiency has become a critical concern. Knowledge distillation (KD) mitigates this issue…
Topology-Guided Knowledge Distillation for Efficient Point Cloud Processing
Luu Tung Hai, Thinh D. Le, Zhicheng Ding +2
Point cloud processing has gained significant attention due to its critical role in applications such as autonomous driving and 3D object recognition. However, deploying high-perfo…
Optimizing Contrail Detection: A Deep Learning Approach with EfficientNet-b4 Encoding
Qunwei Lin, Qian Leng, Zhicheng Ding +2
In the pursuit of environmental sustainability, the aviation industry faces the challenge of minimizing its ecological footprint. Among the key solutions is contrail avoidance, tar…